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There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.

Though the circular economy (CE) is a current buzzword, this still lacks a precise definition. In the absence of a clear notion of what that term includes, actions taken by the government and companies may not be well informed. In particular, those actions need to consider what people mean when people talk about the CE, either to refocus people's decisions or to undertake a more effective communications strategy.

Since people voice people's opinions mainly through social media nowadays, special attention has to be paid to discussions on those media. In this paper, the authors focus on Twitter as a popular social platform to deliver one's thoughts quickly and fast. The authors' research aim is to get the perceptions of people about the CE. After collecting more than 100,000 tweets over 16 weeks, the authors analyse those tweets to understand the public discussion about the CE. The authors conduct a frequency analysis of the most recurring words, including the words' association with other words in the same context and categorise them into a set of topics.

The authors show that the discussion focuses on the usage of resources and materials that heavily endanger sustainability, i.e. carbon and plastic and the harmful habit of wasting. On the other hand, the two most common good practices associated with the CE and sustainability emerge as recycling and reuse (the latter being mentioned far less). Also, the business side of the CE appears to be relevant.

The outcome of this analysis can drive suitable communication strategies by which companies and governments interested in the development of the CE can understand what is actually discussed on social media and call for the attention.

This paper addresses the lack of a standard definition the authors highlighted in the Introduction. The results confirm that people understand CE by looking both at CE's constituent activities and CE's expected consequences, namely the reduction of waste, the transition to a green economy free of plastic and other pollutants and the improvement of the world climate.

This study builds on knowledge-based view (KBV) research and the natural resource-based view of the firm (NRBV) to examine the effect of knowledge absorptive capacity on innovative performance. It also investigates the mediating role of three dimensions of the cluster environment: degree of network, institutional environment and access to factors of production.

By means of partial least squares-based structural equation modelling method, the study validated and analysed the responses of 503 owners and managers of small and medium-sized enterprises (SMEs) in the wood industrial cluster of Cote d'Ivoire, a developing economy.

The analysis and results reveal that knowledge absorptive capacity strongly predicts cluster environment and innovation performance. Moreover, the cluster environment emerged as a powerful determinant of innovation performance and a mediator of the effect of knowledge absorptive capacity on innovation performance. Unequivocally, institutional support has no significant impact on knowledge absorptive capacity (KAC) and innovative performance mediation relationship and is not a key determinant of innovative performance.

This study offers a key departure from past studies by linking knowledge absorptive capacity to innovative performance and the cluster environment in SMEs. It also extends knowledge concerning the role of KBV, NRBV and relational theory in innovation performance.

Providing student housing designed to support students living with a disability is a global challenge. This study assesses buildings' physical health condition systems and drivers of physical health condition effects on students living with disability (SWD) in purpose-built university housing in Ghana.

The study used quantitative design and methods based on the theory of supportive design premises. Using the partial least square structural equation model, a survey of 301 students living with a physical disability, mild visual disability and mild hearing disability was collected in 225 student housings.

The study found that insect control and cleaning services are a priority in off-campus building design and management and directly positively affected the sense of control and physical health of SWD. The nature of lightning systems, noise and thermal comfort directly negatively affected SWD disability learning and discomfort.

Reviewing and enforcing student housing design drawings at the preliminary development stage by university management is critical. More broadly, physical health systems that control cleaning, noise and thermal comfort are essential for SWD health in student housing.

Studies on all-inclusive building designs have consistently focused on lecture theaters and libraries with limited attention on the physical health condition systems in student housing that support the quality healthcare of university campuses. Research on physical health condition systems in student housing is significant for all-inclusiveness and student housing management.

Practitioners and management researchers have chorused the salvific tendencies of spiritual intelligence. Whilst the emergence of spirituality and its derivatives in the workplace is widely acclaimed, the conflict that exists between spiritual ideals and the capitalist ethos of modern organisations raises questions about dark manifestations. This incongruence necessitates the consideration of the misuse of spiritual intelligence.

This paper adopts conceptual lens and theoretical arguments to interrogate the assumption of absolute constructiveness that is accorded spiritual intelligence in its framing and discusses the potential of a dark side.

The dark side of spiritual intelligence is its deployment to achieve self-serving purposes, to harm, rather than to help others. More practitioners and management researchers must acknowledge that spiritual intelligence and workplace spirituality may have dark manifestations and incorporate this reality in the assessment of organisations and the individuals within them.

This exploratory article joins the sparse extant literature on the dark side of spiritual intelligence and workplace spirituality. It contributes to the literature by offering critical insights into spiritual intelligence and the need to integrate the potential for misuse in the existing models.

Outstanding unexercised stock options can motivate managers to engage in actions that increase the value of their company’s stock, including buying back their firm’s stock. The objective of granting stock options to managers is to align their interests with stockholders by tying a portion of their compensation to the company’s stock performance. However, unexercised stock options may have unintended consequences by providing managers with a vested interest in artificially boosting stock prices via stock buybacks. The primary objective of this research is to study the main factors that influence firms' buyback decisions amongst hospitality firms at a time when these firms were clamoring for taxpayer bailouts. Results from logistic regression seem to suggest that outstanding executive stock options are a major contributory factor in a firm’s buyback decision. Estimates also indicate that larger, more profitable firms will likely engage in stock buybacks. These findings survive a battery of tests.

The authors use logistic regression to predict the probability of a firm’s buyback decision based on a given set of exogenous explanatory variables.

The paper supports the hypothesis that buyback decisions are guided by the motive to prop support stock prices in the presence of outstanding restricted stock options/warrants granted to firms' executives.

The paper focuses on the buyback decision of U.S. hospitality firms. The results, therefore, might not be generalizable to firms in other industries or countries.

U.S. share repurchase corporate policy and government regulation needs to be revisited given the economic imperative for firms to invest in activities to restore employment and put them in a position for economic recovery.

Public criticism of the size, structure and form (i.e. loan vs grant) of COVID-19 bailouts warrants an examination of whether the factors that drive hospitality and tourism firms to repurchase shares support economic recovery.

Consistent with agency theory, the authors find a significant positive association between outstanding restricted stocks and a firm’s decision to support the stock prices by buying back shares.

The COVID-19 crisis has sped up digital transformation and technologies by several years. Customers have dramatically shifted to online channels, and businesses have quickly responded by offering additional canals for online shopping and payment. Customers have also been exhibiting greater preferences for contactless payments, and mobile banking has therefore become a norm in both developed and developing countries. This study aims to understand the antecedents of mobile banking actual usage in an early adoption stage setting (i.e. Morocco) through a comprehensive conceptual model combining the unified theory of acceptance and use of technology, the DeLone and McLean IS success model and additional constructs extracted from extent literature. The moderating effects of age, gender and education are also examined and analyzed using multigroup analysis.

Based on data collected from 616 Moroccan users, the authors empirically tested the proposed conceptual model using structural equation modeling.

First, consumer M-banking actual usage has a significant effect on customer satisfaction and attitudinal loyalty; at the same time, attitudinal loyalty was significantly influenced by customer satisfaction. Second, while M-banking actual usage was significantly influenced by effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, service quality, trust, attitude and perceived security, the results show no significant impact of system quality and information quality. Third, the relationship between M-banking actual usage and its antecedents was significantly moderated by age, gender and education.

The findings help bank practitioners to understand the importance of meeting customers’ needs and expectations as a prerequisite in enhancing actual usage, satisfaction and attitudinal loyalty. More importantly, the authors emphasize the need for demographically oriented strategies to target different demographic segments of customers.

The study bridges a gap in M-banking literature by offering a thorough understanding of consumers’ mobile banking use during the pandemic. The findings provide evidence of the applicability of the conceptual model proposed in this research. Furthermore, the reflection of the moderating effects of gender, age and education emphasizes the mobile banking usage disparities among dissimilar demographic segments.

Smart manufacturing is revolutionizing the manufacturing industry by shifting the focus from traditional manufacturing to a more intelligent, interconnected and responsive system. Despite being the backbone of the economy and despite the government’s efforts in supporting and encouraging the transformation to smart manufacturing, small and medium enterprises (SMEs) have been struggling to transform their operations. This study aims to identify the challenges for SMEs’ transformation and the benefits they can get from this transformation, following a systematic review of existing literature.

A systematic review of existing literature has been performed to identify the peer-reviewed journal articles that focus on smart manufacturing for SMEs. First, a comprehensive list of keywords relevant to the review questions are identified. Second, Scopus and Web of Science databases were then used to search for articles, applying filters for English language and peer-reviewed status. Third, after manually assessing abstracts for relevance, 175 articles are considered for further review and analysis.

The benefits and challenges of SMEs’ transformation to smart manufacturing are identified. The identified challenges are categorized using the Smart Industry Readiness Index (SIRI) framework. Further, to address the identified challenges and initiate the SME’s transition toward smart manufacturing, a framework has been proposed that shows how SMEs can start their transition with minimum investment and existing resources.

Several studies have concentrated on understanding how smart manufacturing enhances sustainability, productivity and preventive maintenance. However, there is a lack of studies comprehensively analyzing the challenges for smart manufacturing adoption for SMEs. The originality of this study lies in identifying the challenges and benefits of smart manufacturing transformation and proposing a framework as a roadmap for SMEs' smart manufacturing adoption.

This study aims to examine the impact of perceived risk dimensions, confirmation, perceived usefulness and perceived ease of use on user satisfaction and their continuance intention to use mobile payments across Vietnam based on the extended technology continuance theory (TCT).

This study used an online questionnaire-based survey design to collect data from 417 respondents using judgmental and snowball sampling techniques. The respondents in this survey are personal users of mobile payments across Vietnam. Data analyses and hypothesis testing were carried out using the partial least squares structural equation modeling.

The findings demonstrate that physical risk, time loss risk, opportunity cost risk, confirmation, perceived ease of use and perceived usefulness are important elements influencing consumers’ satisfaction toward continuance intentions to use mobile payment services. Satisfaction is also significantly associated with continuance intentions to use mobile payments across Vietnam. Other relationships, including functional risk, social risk, financial risk and information risk are not significantly related to satisfaction. These results are expected to be useful for mobile payment service providers. Understanding the factors mentioned in this study enables mobile payment service providers to improve their offerings strategically and then motivate their clients to keep using mobile payments.

The work is among the very few bodies of empirical research to investigate the continuance intention to use mobile payments using the extended TCT by incorporating the various dimensions of perceived risk construct in the fintech sector to develop a research model for this study. Furthermore, combining with perceived risk dimensions, this study expands the TCT model’s mobile app to the fintech sector, and advances the understanding of the use of the extended TCT in the fintech sector and adds to the theory.